The present invention relates to a method and apparatus for determining the distribution of constituent subpopulations within a population of particles having overlapping subpopulations.
In both industry and science, it is frequently necessary that information be obtained regarding the distribution of constituent subpopulations within a diverse population of particles. For example, in the field of medicine, it is possible to detect abnormalities in a patient's blood by measuring the distribution of various subpopulations of white blood cell species that are present therein. Typically, such information is obtained using a particle distribution analyzer, such as the one described in U.S. Pat. No. 4,491,926 to Okada et al., which is specifically incorporated herein by reference.
Such analyzers typically include a detector which is adapted to detect particles by electrical or optical differences from a medium containing the particles in dispersion and to generate signals proportional to the differences, a parameter extraction circuit which is adapted to measure the signal corresponding to each particle, an analog to digital converter for converting the measured signal into digital form for processing, and a memory for storing the information corresponding to each particle. Optionally, the analyzer may further include a histogrammer, which is used to process the information into the form of a histogram. Histograms are graphic representations of frequency distributions in which the widths of contiguous vertical bars are proportional to the class widths for a selected property and the heights of the bars are proportional to the class frequencies. By comparing the histogram obtained for the sample to a reference histogram, one may draw a conclusion regarding the normalcy of the sample.
Unfortunately, in many situations, two or more of the subpopulations within the sample possess overlapping ranges with respect to the property being measured. For example, in the case of white blood cells, the size ranges for the various varieties overlap considerably (e.g., variety 1 ranges in size from 100 femtoliters to 325 femtoliters; variety 2 ranges in size from 75 femtoliters to 125 femtoliters; etc.). Because of this overlap, a histogram will, to a lesser or greater extent, merge the representations of the subpopulations, making it impossible to accurately determine the distribution of or, in some cases, the existence of the constituent subpopulations. These merged subpopulations are frequently referred to in the art as hidden, overlapping, or poorly defined subpopulations.
One approach to this problem has been to resolve the overlapping subpopulations by measuring an additional property which does not result in overlap of the same subpopulations. For example, in the case of white blood cells, opacity and/or density may be measured in addition to size. As can readily be appreciated, this approach suffers from being both time-consuming and costly since the analytical equipment must be capable of making the various types of measurements described above for each particle.
Another approach to this problem has been to resolve the overlapping subpopulations into their constituent subpopulations using mathematical models which truncate the crude data. For example, U.S. Pat. No. 4,706,207 to Hennessy et al., which is specifically incorporated herein by reference, describes a method which involves counting the number of objects in a particular "channel" (a very limited band of objects), making similar counts in adjacent channels, employing cutoff points made at selected ends of the normal curve within regions where other objects are not usually detected, and then extrapolating the rest of the curve based on the typical shape of known object distribution curves. The shortcomings of this method are that not all the raw data are used in the analysis and that, in the normal situation, points obtained in the log versus delta log plot will not fall strictly along a straight line, making it necessary to find a mean value straight line. In addition, in using this technique, criteria about whether certain counts should be taken or discarded have to be developed. Consequently, only a rough estimate of the distribution of the overlapping subpopulations can be determined with this method.